Optimization of content representation in a user interface

ABSTRACT

Methods and systems are described for providing optimal representations of content. A user interface may present content based on one or more images representing the content. User interactions associated with the content may be tracked based on which of the one or more images was used to represent the content. Statistical information may be tracked to determine which groups of users respond to particular images used to represent content. The statistical information may be used to select which images are used to represent the content for additional users.

BACKGROUND

Content systems, such as those associated with streaming contentsystems, DVRs, fiber and cable systems and the like, typically usegraphical user interfaces to allow users to navigate, review and selectcontent. Often, content creators such as a movie or television (TV)studio will supply multiple images to represent particular content, suchas a movie or TV show. These images can have different sizes and includedifferent cast members and the like. The media presentation providerwill then select an image to represent the content, typically based onbackground or size. However, improvements in the selection and displayof images via graphical user interfaces are needed.

SUMMARY

In a user interface, content, such as a movie or television show, may berepresented by one or more images along with text describing thecontent. Some users may respond differently based on which of the one ormore images are used to represent the content. The present disclosurerelates to methods and systems for determining an optimal image (e.g.,or preferred image) to represent content to engage user interest. Theoptimal image may be determined based on user information, such asstatistical information, demographics, viewing history, and otherinformation.

The present methods and systems can be used to determine the optimalimage to represent content for a particular member of a characteristicgroup, such as a demographic group. A variety of images may be providedto different members of a characteristic group (e.g., a statisticalgroup). Navigation data related to the selection of content andassociated images may be collected for members of the characteristicgroup to determine which images are more likely to engage interest incontent for members of the characteristic group. The navigation data canthen be used to determine optimal or preferred images for other membersof the characteristic group.

The navigation data may be collected in response to user interactionswith a user interface, such as selecting an image tile representing thecontent in a menu, or requesting to access the content. Indications ofthe user interactions associated with the image in the user interfaceand associated user information can be stored. The stored indicationscan be used to determine an optimal image to represent content for othermembers of the characteristic group. The optimal image may then besupplied to other members of this characteristic group. Such adetermination of an optimal image using these operations can be done formultiple characteristic groups.

Providing an optimal image to members of a characteristic group canresult in increased consumer usage of a content system since users willfind more content that looks interesting. Such increased consumer usagecan result in improved customer loyalty and retention.

Additional advantages will be set forth in part in the description whichfollows or may be learned by practice. It is to be understood that boththe foregoing general description and the following detailed descriptionare exemplary and explanatory only and are not restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments and together with thedescription, serve to explain the principles of the methods and systems.

FIG. 1A is a block diagram illustrating an example system.

FIG. 1B is a block diagram illustrating another example system.

FIG. 2A shows an example user interface with an image.

FIG. 2B shows an example wither with an alternate image.

FIG. 3A is a flow diagram illustrating an example method.

FIG. 3B is a flow diagram illustrating another example method.

FIG. 4 is a flow diagram illustrating another example method.

FIG. 5 is a flow diagram illustrating another example method.

FIG. 6 is a flow diagram illustrating another example method.

FIG. 7 is a flow diagram illustrating another example method.

FIG. 8 is a block diagram illustrating an example computing device.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Providing images that specifically appeal to the members of a group(e.g., demographic group), rather than users as a whole, allows fordifferent demographic groups to be given different preferred images.This approach provides for a more personalized and appealing contentuser interface to the members of the different characteristic groups,such as demographic groups.

For example, if a specific piece of content has multiple associatedimages, the system may determine that midwestern men select the contentmore often when image A is used; while west coast women select thecontent more often when image B is used. This information can be used tocustomize a user interface such that, thereafter, midwestern men seeimage A and west coast women see image B associated with the content.Thus, both groups will see an associated image that they would prefer.

Statistical data of users of a user interface may be used to determinewhich images to supply to the user. The users may be associated withcharacteristic groups. The characteristic groups may represent incomedistinctions, age distinctions, and location information. Thestatistical information can be obtained from user information providedto a content provider.

The content system can be network or cloud system, by which a contentprovider, such as a cable television service provider, receives requeststhrough a user interface and provides content for playback. Othersystems, such as a content system, may implement aspects of the presentdisclosure. Content may comprise a content asset or program. Forexample, the content may comprise a television show, a movie, a sportsevent broadcast, or the like. As used herein, content may additionallyinclude a portion of a program or content asset.

FIG. 1A shows an interface server 102 or computing device that providesimages and other data that allows a user device 104 to construct a userinterface, such as a graphical user interface. For example, theinterface server 102 may provide images and other data that allows theuser device 104 to populate user interface templates to produceinterface pages that allow the user to select content. The interfaceserver 102 may be associated with a content server 108 that providescontent, e.g., video, audio, programs, shows, applications. Theinterface server 102 may generate a portion or all of the userinterface, which may be transmitted to the user device 104. The userinterface may be part of a content selection system that allows the userto select content to access using menus and the like. The user interfacemay sort content by genre and/or network. The user interface maycomprise a content recommendation system which is an informationfiltering system that seeks to predict content of interest to the user.

The user interface may comprise interface elements associated withcontent, such as movies, audio, programs, shows, newscasts, sportscasts,social media, and/or the like. The interface elements may comprisebuttons, links, windows, boxes, menus, lists and/or the like. Theinterface elements may comprise an image element (e.g. window, box) thatdisplays an image. The image may be associated with content. The imageelement may be presented with the content on a page (e.g., dedicated toa specific content asset), in a menu item (e.g., as part of a menu).

A user interaction (e.g., click, selection) can be used to instruct thecontent server 108 to provide interface data to the user device. A userinteraction may cause the user interface to navigate to a page withdetails about the selected content.

The user interactions may be transmitted to and/or received by acomputing device such as the interface server 102. Alternately, userinteractions may be transmitted to, processed by, or stored at anotherserver or computing device. The servers can include functionalityimplemented at one or more server devices for client devices. Theservers, such as interface server 102 and content server 108, cancomprise one or more computing devices that can implement the methodsdescribed herein.

The user device 104 may output content to the user. The user device 104may receive a user interaction indicating a request for content from theuser. The user device 104 may transmit a request for the content to thecontent server 108. The content server 108 may transmit the content tothe user device 104. The content may be transmitted as a content stream,a content file, and/or the like. The user device 104 may comprise adisplay and/or be in communication with a display. The content may berendered, presented, and/or the like to the user via the display.

The user device 104 may comprise a display device, a television, a settop box, a streaming media device, a smart device (e.g., smart wearable,smart glasses), mobile phones, onboard device (e.g., vehicleentertainment system), a tablet, a laptop, a computing station, and/orthe like. The user device 104 may be configured to output (e.g.,display, render, present) the user interface to users. The user device104 may be configured to receive a user interaction with the userinterface. The user interaction may comprise selection of an interfaceelement (e.g., a button, a link, a window). The user interaction maycomprise a selection of content from a menu (e.g., or a list) of contentassets. The user interaction may comprise a navigation command, such asnavigating away from content (e.g., a back button, scrolling in adirection (e.g., up, down, left, right) away from content. The userinteraction may comprise hovering over content. The user interaction maycomprise delaying to navigate. For example, a user may stop providinguser interactions while viewing at a menu item representing particularcontent. The user device 104 may store one or more of the userinteractions as navigation data. The navigation data may comprise acontext of the user interaction. The context may comprise a sequence ofuser interactions before and/or after the user interaction. The contextmay comprise a menu, a submenu, a page, and/or the like in which anassociated user interaction is received. For example, the context mayindicate that a user selected an image element from a menu to access acontent page associated (e.g., dedicated to) the content asset. Thespecific menu and/or menu type may be indicated in the context. Forexample, the menu may comprise a grouping of content, such as bycategory, viewing pattern (e.g., suggestion based on previously viewedcontent), popularity, and/or the like. The navigation data may comprisea content identifier associated with the content. For example, thenavigation data may comprise a content identifier for content that auser requested to access, a content identifier for content that a userdid not request to access (e.g., the user passed over or otherwiseviewed an image tile representing the content, perhaps while navigatinga menu).

The user device 104 may transmit the navigation data (e.g., indicatingselections) to the interface server 102. The user device 104 maytransmit the navigation data. The navigation data may be transmitted inresponse to an event, such as a user interaction (e.g., user selects acontent item from a menu, user selects a button to request rendering ofthe content). The navigation data may be transmitted based on apredetermined schedule, a request from the interface server 102, and/orthe like. The user device 104 may transmit user information (e.g., withthe navigation data) to the interface device 102. The user informationmay comprise demographics, such as age, nationality, gender, location,and/or the like. The user information may comprise account information,such as subscription tier, purchase history, user settings, scheduledcontent recordings, social media information, and/or the like.

The interface server 102 may be configured to receive (e.g., together orseparately) the navigation data and/or the user information (e.g., userinformation associated with the navigation data) from the user device104. The interface server 102 may be configured to store navigation dataand/or user information in a data store 122, such as a database, a file,and/or the like. Other storage devices may be used, such as volatilememory (e.g., random access memory (RAM)), a hard disk drive, anetwork-attached storage (NAS), and/or a storage area network (SAN) uponwhich the content or portions thereof may be stored.

The interface service 102 may be configured to generate predictive data(e.g., or associative data) based on the navigation data, userinformation, and/or the like. For example, the interface server 102 maybe configured to store an association between one or more of anidentifier of content (e.g., selected or not selected by the user), anidentifier of an image used to represent the content, a user identifier,a user interaction (e.g., selected content from a menu, accessedcontent, navigated back to the menu from the content, did not accesscontent), a navigation context (e.g., menu, submenu, page), userinformation (e.g., demographic identifier, group identifier).

The predictive data may comprise statistical information based on thenavigational data, user information, and/or the like. The predictivedata may comprise statistical information based on user interactions,the context associated with the user interaction, the content associatedwith the user interaction, the image used to represent the content, userinformation, a combination thereof, and/or the like. The statisticalinformation may comprise counts (e.g., or other user interest metric)associated with characteristic groups (e.g., statistical groups). Forexample, the navigational data and user information received for aspecific user interaction may be analyzed to determine a characteristicgroup. For example, demographic information associated with the userperforming the user interaction may be used to match (e.g., associate) aparticular user interaction with a characteristic group. The predictivedata may comprise a plurality of characteristic groups. Thecharacteristic groups may be predefined or may be learned, via machinelearning or other statistical analysis. The specific user interactionmay be matched to one or more characteristic groups. Each of the one ormore characteristic groups may be associated with a count indicative ofa number of user interactions associated with the particularcharacteristic group. The count may be incremented for each of the oneor more characteristic groups that match a particular user interaction.

The interface server 102 may be configured to determine an optimal imagefor a user or user group based on the predictive data (e.g., navigationdata, user information, associations, groupings, statisticalinformation). Alternately or additionally, another device may receive,process, and/or store the information stored in the data store 122. Theoptimal image may comprise an image associated with a highest likelihood(e.g., highest probability, highest count) of engaging (e.g., orcausing) interest of a user to interact (e.g., request, access) withparticular content. The likelihood may be specific to a particularcharacteristic group that matches the user. The optimal image may bedetermined based on determining an image that has a highest count (e.g.,of positive user interactions) for a particular characteristic group towhich the user belongs. Thus, the optimal image may vary based on theuser.

The statistical information may be tracked for a plurality of imagesassociated with the content. For example, each content asset may have acorresponding plurality of images for representing the content in theuser interface. Different characteristic groups may be used to trackuser interactions for different content. For example, for sportscontent, characteristic groups may be based on user locations. For newscontent, characteristic groups may be determined based on userinterests. If a user requests interface data (e.g., content related datafor a menu or content page), the interface server 102 may determine theoptimal image for a particular user to represent content based onstatistical information at the time of the request for interface data.The optimal image for a particular user may change over time as thestatistical information is updated, as the user is grouped differently,and/or the like. If a user belongs to multiple characteristic groups,the optimal image may be determined based on a combination of countsassociated with the multiple groups. The combination may compriseadditional of the counts, a weighted average of the counts, anon-weighted average of the counts, and/or the like. The counts trackedin the statistical information may be positive or negative. For example,a negative user interaction, such as a user navigating past or otherwiseignoring an image representing content, may be associated with anegative count. A positive user interaction, such as a user requestingclicking on an image element representing content or requesting toaccess the content, may be associated with a negative count.

The data store 122 may comprise a first table (such as Table 1 discussedbelow) that indicates user interactions (e.g., content selections) for aspecific image associated with the content for each characteristicgroup. As additional navigation data is received, by the interfaceserver 102, the interface service 102 may generate and/or update thefirst table. For example, for each image used to represent particularcontent, a count of the number of user interactions may be updated forone or more characteristic groups.

The data store 122 may also comprise a second table that associates useridentifiers with characteristic groups, such as demographic groups. Userinformation sent by the user device 104, or other information, such asregistration information (e.g., data from another source) can be used todetermine the characteristic group for a user (e.g., or user device104). If navigation data is received for a particular user (e.g., oruser device 104), the user identifier for the user can be used to lookup an associated characteristic group in the second table. Then, a countor other metric in the first table may be updated for an associatedcharacteristic group.

FIG. 1B shows details of an exemplary local system 120. The local system120 can be connected to the interface server 102 and content server 108through a content delivery system 140, such as a cable system, satellitesystem, Internet Protocol (IP) delivery system, phone or cellularsystem.

The local system 120 can include a modem 124 connected to a localnetwork 126. The modem 124 can interact with the specific type ofcontent delivery system 140. For example, the modem 124 can be a cablemodem, a satellite modem, or the like. Alternately, the local devicesneed not use a modem to connect to the interface server 102 and contentserver 108.

Local devices, such as local devices 128, 130 and 132, can connectthrough the local network 126 to receive video presentations and userinterface data. The local network 126 can be a wireless network or awired network. The local devices, such as local devices 128, 130 and132, can construct the user interfaces using the user interface dataincluding images. The local devices 128, 130, and 132 may comprise theuser device 104 of FIG. 1A. For example, the local devices 128, 130, and132 may be configured to perform any of the functionality described forthe user device 104 of FIG. 1A.

The local system 120 need not include a modem 120 or a local network126. For example, the local system 120 can be a local device such as acomputer or a mobile phone that connects to a cellular or Wi-Fi network.

It will be appreciated that the device used to request that the contentbe provided in the system may be distinct from the device used toreceive the content for playback. To illustrate, a user may use his orher local device (e.g., set-top cable box or other computing device) torequest that a particular content be provided in the system, but maylater request and playback the content with software running on his orher smart phone. The device may be connected to the system via anysuitable network, which may comprise, for example, a cable network,satellite network, and/or the Internet.

In one example, the interface server 102 can provide user interface dataincluding images to multiple local systems through the contenttransmission system 142 to local systems. Multiple members of ademographic group can receive user interface pages, some receiving imageA (for example, a close-up of an actor) and some receiving image B (forexample, a group photo).

The selections of the content associated with the images can be sentthrough the content transmission system to the interface server 102 toultimately be stored at database 122.

FIG. 2A and FIG. 2B show examples of user interfaces with alternateimages representing the same content. FIG. 2A shows a user interface 202with image A. FIG. 2B shows a user interface 204 with image B. Asdescribed herein, the images, such as image A of user interface 202 orimage B of user interface 204, can be one of multiple images that can beassociated with particular content, such as a movie, a show, a program,a newscast, a sportscast, a media clip, and/or the like. If a userinteracts with (e.g., selects, requests) content from a user interface,an indication of the associated image, such as image A of user interface202 or image B of user interface 204, can be transmitted to theinterface server 102. The example of FIG. 2A and FIG. 2B shows twodifferent images but more than two images could be used to represent thecontent.

In one example, a situational comedy may be represented with multipleimages, such as an image emphasizing the parents (e.g., image A) and animage emphasizing the children (e.g., image B). Members of differentdemographic groups may be more attracted to different aspects of a show.For example, teenagers may be more attracted by image A emphasizing thechildren in the situation comedy while adults may be more attracted byimage B emphasizing the parents in the situation comedy. As describedbelow in FIG. 3A, FIG. 3B, and FIG. 4, the selection of images to play aprogram (or to learn more about a program) of members of a demographicgroup can be used to determine the images to provide to other members ofthe demographic group.

In reference to FIG. 3A, at step 302, a request for content (e.g., avideo presentation) is received. The content may be associated with oneof multiple images, such as image A from user interface 202. The requestmay comprise an indication of which image was provided to the user.Alternately, the image ID may be stored at the server associated with auser ID and the image ID may be derived from the user ID.

In step 304, an indication of the request associated with the one ofmultiple images and a demographic group of a requester may be stored.The indication may be stored, permanently or temporarily, in memory or adatabase. The indication may be an updated counter value or a temporaryindication that is used to determine an updated counter value or someother indication.

Steps 302 and 304 may be performed in a test period. For example, duringa test period, image A may be randomly provided to half of the membersof a demographic group that requests a user interface page associatedwith content. Image B can be provided to the other half of the membersof a demographic group that requests a user interface page associatedwith the content. During the test period, the system may determinewhether image A (a close-up of an actor) or image B (for example, agroup photo) receives more positive user interactions (e.g.,selections). For example, among members of a demographic group, image Acould have a 29% click-through rate and image B could have a 40%click-through rate, and it can be determined that image B is to bepreferred for that demographic group. After the test period, thetabulated selections may be used to provide a preferred image to otherusers in the demographic group in step 306.

The testing can be concurrent with providing preferred images to otherusers as described below. For example, certain users may receive randomimages for testing while other users receive the preferred images forthe demographic group associated with the users.

In step 306, the stored indication may be used to determine an image(e.g., associated with the content) to provide to another member of thedemographic group. For example, an updated count associated with one ofmultiple images can be used to calculate whether to provide that imageor another image of the multiple images.

FIG. 3B shows an example implementation of step 306. In step 306 a, ademographic group may be determined for a user. For example, thedemographic information may be derived from subscriber information. Auser ID in the request for an updated user interface or user interfacepage can be used to do a look-up of the user's demographic category.

In step 306 b, the demographic information may be used to select apreferred image for a user interface page. For example, five hundred(500) members of a demographic group may be provided user interface 202with image A. Thirty seven (37) members of the demographic group maywatch the associated movie. Five hundred (500) members of thedemographic group may be provided user interface 204 with image B.Fifty-six (56) members of the demographic group may watch the associatedmovie. In this scenario, it may be determined that image B in userinterface 204 is more persuasive/desirable to members of the demographicgroup.

The result may be different for different demographic groups. Forexample, 500 members of another demographic group may be provided userinterface 202 with image A. Forty two (42) members of the additionaldemographic group may watch the associated movie. 500 members of theadditional demographic group may be provided user interface 204 withimage B. Thirty five (35) members of the additional demographic groupmay watch the associated movie. In this scenario, it may be determinedthat the image A in user interface 202 is more attractive to members ofthe second demographic group.

In step 306 c, the preferred image may be provided so that the userinterface page can be generated for the user. The preferred image may bepart of user interface information or a user interface (or userinterface page) that is provided to the user.

In step 306 d, any selections of content from the user interface pagemay then be received and processed. For example, any selections ofcontent can cause a download of this content. Further, the selectionscan also be used to update the preferred image data as discussed above.

In reference to FIG. 4, at step 402, multiple user interface pages maybe provided for content to different users using different images. Atstep 404, selections of content may be received. For example, in oneembodiment, a subset of a first demographic group may be provided userinterface 202 with image A and another subset of the first demographicgroup can be provided user interface 204 with image B.

In step 406, indication of user interactions (e.g., selections) may bestored. The indication may comprise a content ID, an Image ID, anddemographic information. An example set of data for a images associatedwith specific content (e.g., a content asset) are provided below. A realsystem can use significantly more demographic features and images, butfor the ease of display only a few are shown in Table 1 below.

TABLE 1 Mid- Con- $10,000- $50,000- $100,000- At- New West tent Image$50,000 $100,000 $150,000 lantic York Coast 1234 1 1 1 0 2 0 0 1234 2 00 1 0 1 0 1234 3 0 0 0 0 0 0 1234 4 2 0 0 1 0 1 1234 5 0 1 3 1 2 1

In this example, “$10,000-$50,000”, “$50,000-$100,000”, and“$100,000-$150,000” are income brackets and “Mid-Atlantic”, “New York”and “West Coast” are indications of location. These are exampledemographic groups (e.g., or characteristic groups). The tablereferences multiple images (images 1-5) for a particular content(content 1234). Associated feature counts can be maintained fordifferent demographic groups.

As members of the demographic groups select content associated with theimages presented in the user interface, the selections can be added tothe table. This information may be used to produce a preferred imagewhich is provided to the other members of the Demographic groups.

As more user interactions are received, the feature counts may increase,allowing for the determining of an optimal image (e.g., or a preferredimage) for different demographic groups. The optimal image may beprovided to members of the demographic group. The optimal image may besent in response to a user interface request from users in the specificdemographic groups. A simple learning technique would allow fordynamically presenting the images that produces the highest click thru,and ultimately the highest view rates.

In step 408, the stored indications may be used to determine whichimages are preferred by members of a demographic group. In the exampleof Table 1, the income bracket $100,000-$150,000 show a preference forimage 5. The Mid-Atlantic demographic group shows a preference for image1.

Such tables could be used for each of the content served by a contentsystem. In example of table 1, there are five images. The images 1-5 maybe randomly provided to different members of the demographic groupsduring a test period.

Table 1 shows two demographic categories: income and location. Otherdemographic categories may be used as well. Users may be part of ademographic group in each category. For example, a user may be in the“$100,000-$150,000” demographic group and the “Mid-Atlantic” demographicgroup. One option is to split the demographic groups into subgroups. Forexample, the three (3) location groups and three (3) income groups canbe split into nine (9) subgroups. Alternately, the selections fordifferent categories can be combined when the preferred image is to beprovided to a user. The combination can be weighted or unweighted.

In step 410, the user interface page for content with the optimal imagemay be provided to members of the demographic group. For example,optimal images may be provided for each demographic group to members ofthe demographic groups. For Table 1, the income bracket“$100,000-$150,000” shows a preference for image 5. The “Mid-Atlantic”demographic group shows a preference for image 1. If a user is a memberof both groups then one of the categories could have preference or acombination could be used. An unweighted combination of the selectionsfor the income bracket “$100,000-$150,000” and “Mid-Atlantic”demographic group would have image 5 as the selected image.

A/B testing can be used to determine which of the multiple images getsselected more by the members of each demographic group. A/B testing is aterm for a randomized experiment such as with two variants, A and B,which are the control and variant in the controlled experiment. A/Btesting is a form of statistical hypothesis testing with two variants.Other terms used for this method include bucket tests and split-runtesting. The A/B testing can also include the testing of more than twovariants. The A/B testing can be automatically done with candidateimages as input.

In reference to FIG. 5, at step 502, a first image (e.g., or dataindicating the first image) of a plurality of images associated with acontent asset may be transmitted. The first image may be transmitted toa user interface associated with a first user. The first image may betransmitted by a content device, such as a content server, applicationserver, and/or the like. The first image may be a representation of thecontent asset. The user interface may be configured to output the firstimage as a representation of the content asset. A user device maycomprise the user interface. The user device may comprise a set top box,a television, a content streaming device, onboard device (e.g., vehiclemedia system), a mobile device, a laptop, tablet device, a computingstation, a smart device (e.g., a smart phone, smart glasses, smartwatch), a virtual reality device, and/or the like. The content asset maycomprise a video asset (e.g., show, movie, program, sports event), anaudio asset (e.g., newscast, podcast, music), an application (e.g.,game, app), a document (e.g., social media text, news, information,book), and/or the like.

Transmitting, to the user interface associated with the first user, thefirst image may be performed in response to receiving a request for datato update a menu or a page of the user interface associated with thefirst user.

At step 504, an indication of a user interaction with the user interfacemay be received (e.g., by the content device). The user interaction maybe indicative of a response of the first user to the first image. Theuser interaction may comprise selection of a tile in a menu of the userinterface. The tile may comprise the first image. The user interactionmay comprise a positive interaction, a negative interactions (e.g.,navigating past, navigating away from, navigating back to a menu). Theinteraction may comprise hovering, clicking, selecting, and/or the like.For example, the user interaction may comprise requesting output of thecontent asset. The indication of the user interaction with the userinterface may comprise a menu context of the user interaction. The menucontext may comprise a type of menu (e.g., list of content assets,content page for a specific content asset).

At step 506, statistical information associated with the content assetmay be updated (e.g., by the content device). The statisticalinformation may be updated based on the indication of the userinteraction. The statistical information may be updated based on acharacteristic group associated with the first user. The characteristicgroup may be determined based on the user interaction. Thecharacteristic group may be determined based on a characteristic of thefirst user. The characteristic group may be determined based on acharacteristic of the user device that transmitted the request. Thecharacteristic group may be determined based on a user interface contextassociated with initiating the request. The characteristic group may bedetermined based on other factors, such as timing, the content assetrequested, and/or the like.

The characteristic group may comprise a demographic group. Thecharacteristic group may comprise a group associated with acharacteristic, such as a user characteristic, a device characteristic,a browsing history characteristic, a subscription characteristic, aninterface context (e.g., type of interface element, category or genreassociated with an interface element). The characteristic may comprisean age, an income bracket, an occupation, a location, a user affinitygroup (e.g., sports team, political association), a combination thereof,and/or the like. The characteristic may comprise a type of device (e.g.,mobile), operating system, power level, user interface version, acombination thereof, and/or the like. The characteristic may comprise atime of day, time of the month, season, and/or the like.

Updating the statistical information may comprise updating a userinteraction metric associated with the first image and associated withthe characteristic group. The user interaction metric may comprise acount of a number of user interactions (e.g., specific to users of thecharacteristic group) associated with the first representation. Forexample, the user interaction metric may comprise a number of times anyuser associated with the characteristic group requested the contentasset when the first image was used in the user interface to representthe content asset. The user interaction metric may comprise a number oftimes any user associated with the characteristic group selected aninterface element (e.g., a menu tile) comprising the first image tonavigate to a page describing the content asset. The user interactionmetric may represent positive interactions, negative interactions (e.g.,navigating past, navigating away from, navigating back to a menu), ormay represent a combination of positive interactions and negativeinteractions.

The method 500 may further comprise determining to represent the contentasset by the first image for the second user. The first image may bedetermined based on being associated with a highest statistical value ofthe plurality of images for the characteristic group. The firstrepresentation may be determined by combining (e.g., averaging, adding,multiplying) statistical values associated with different characteristicgroups. For example, more than one characteristic group may bedetermined for a particular request, user, and/or the like.

At step 508, the first image may be transmitted (e.g., by the contentdevice). The first mage may be transmitted for representing the contentin the user interface for a second user. The second user is associatedwith the characteristic group. The first image may be transmitted torepresent the content in the user interface for the second user based onthe second user being associated with the characteristic group. Thefirst image may be transmitted based on the statistical information.Transmitting the first image may be based on determining to representthe content asset by the first image for the second user.

In reference to FIG. 6, at step 602, a request for interface data may bereceived. The request may be received from a user interface associatedwith a first user. Receiving, from the user interface associated withthe first user, a request for interface data may comprise receiving arequest for the interface data to update a menu or a page of the userinterface associated with the first user.

The request for interface data may be received by a content device, suchas a content server, application server, and/or the like. A user devicemay comprise the user interface. The request may be received from theuser device. The user device may comprise a set top box, a television, acontent streaming device, onboard device (e.g., vehicle media system), amobile device, a laptop, tablet device, a computing station, a smartdevice (e.g., a smart phone, smart glasses, smart watch), a virtualreality device, and/or the like.

At step 604, a content asset to represent (e.g., via the user interfacemay) be determined (e.g., by the content device). The content asset torepresent may be determined based on the request. The request maycomprise an identifier of the content asset. The content asset maycomprise a video asset (e.g., show, movie, program, sports event), anaudio asset (e.g., newscast, podcast, music), an application (e.g.,game, app), a document (e.g., social media text, news, information,book), and/or the like.

At step 606, a characteristic group associated with the first user maybe determined (e.g., by the content device). The characteristic groupmay comprise a demographic group. The characteristic group may comprisea group associated with a characteristic, such as a user characteristic,a device characteristic, a browsing history characteristic, asubscription characteristic, an interface context (e.g., type ofinterface element, category or genre associated with an interfaceelement). The characteristic may comprise an age, an income bracket, anoccupation, a location, a user affinity group (e.g., sports team,political association), a combination thereof, and/or the like. Thecharacteristic may comprise a type of device (e.g., mobile), operatingsystem, power level, user interface version, a combination thereof,and/or the like. The characteristic may comprise a time of day, time ofthe month, season, and/or the like.

Determining the characteristic group associated with the user maycomprise determining a correspondence between user informationassociated with the user and a characteristic associated with thecharacteristic group. The characteristic group may be determined basedon a characteristic of the first user. The characteristic group may bedetermined based on a characteristic of the user device that transmittedthe request. The characteristic group may be determined based on a userinterface context associated with initiating the request. Thecharacteristic group may be determined based on other factors, such astiming, the content asset requested, and/or the like.

At step 608, statistical information associated with the content assetand the characteristic group may be determined. The statisticalinformation may indicate responses of users associated with thecharacteristic group to a plurality of images used to represent thecontent asset. The plurality of images may comprise a first image. Thestatistical information may be based on prior user interactionsassociated with the plurality of images.

Determining the statistical information may comprise determining a userinteraction metric associated with the first image and associated withthe characteristic group. The user interaction metric may comprise acount of a number of user interactions (e.g., specific to users of thecharacteristic group) associated with the first representation. Forexample, the user interaction metric may comprise a number of times anyuser associated with the characteristic group requested the contentasset when the first image was used in the user interface to representthe content asset. The user interaction metric may comprise a number oftimes any user associated with the characteristic group selected aninterface element (e.g., a menu tile) comprising the first image tonavigate to a page describing the content asset. The user interactionmetric may represent positive interactions, negative interactions (e.g.,navigating past, navigating away from, navigating back to a menu), ormay represent a combination of positive interactions and negativeinteractions.

The method 600 may further comprise determining to represent the contentasset by the first image for the first user. The first image may bedetermined based on being associated with a highest statistical value ofthe plurality of images for the characteristic group. The firstrepresentation may be determined by combining (e.g., averaging, adding,multiplying) statistical values associated with different characteristicgroups. For example, more than one characteristic group may bedetermined for a particular request, user, and/or the like.

At step 610, the first image may be transmitted (e.g., by the contentdevice, to the user device). The first image may be transmitted forrepresenting the content asset in the user interface for the first user.The first image may be transmitted based on the statistical information.Transmitting the first image may be based on determining to representthe content asset by the first image for the first user. Determining torepresent the content asset by the first image for the first user may bebased on the statistical information.

In reference to FIG. 7, at step 702, data indicative of a firstrepresentation of a content asset may be transmitted. The dataindicative of the first representation of the content asset may betransmitted by a content device, such as a content server, applicationserver, and/or the like. The data indicative of the first representationof the content asset may be transmitted to a user interface associatedwith a first user. A user device may comprise the user interface. Theuser device may comprise a set top box, a television, a contentstreaming device, onboard device (e.g., vehicle media system), a mobiledevice, a laptop, tablet device, a computing station, a smart device(e.g., a smart phone, smart glasses, smart watch), a virtual realitydevice, and/or the like. The content asset may comprise a video asset(e.g., show, movie, program, sports event), an audio asset (e.g.,newscast, podcast, music), an application (e.g., game, app), a document(e.g., social media text, news, information, book), and/or the like.

The data indicative of the first representation may comprise an image,an interface configuration (e.g., arrangement and/or location ofinterface elements), a uniform resource identifier (e.g., link) toretrieve the representation, a template, a color scheme, a textualdescription of the content asset, a video clip, and audio clip, and/orthe like.

At step 704, a request for the content asset may be received (e.g., bythe content device, from the user device). The request may be receivedbased on the first representation. The request may be triggered when thefirst representation is presented to the user. The request for thecontent asset may comprise a request to access a user interface pageassociated with the content asset. The request for the content asset maycomprise a request to output at least a portion of the content asset.

At step 706, a characteristic group may be determined (e.g., by thecontent device). The characteristic group may comprise a demographicgroup. The characteristic group may comprise a group associated with acharacteristic, such as a user characteristic, a device characteristic,a browsing history characteristic, a subscription characteristic, aninterface context (e.g., type of interface element, category or genreassociated with an interface element). The characteristic may comprisean age, an income bracket, an occupation, a location, a user affinitygroup (e.g., sports team, political association), a combination thereof,and/or the like. The characteristic may comprise a type of device (e.g.,mobile), operating system, power level, user interface version, acombination thereof, and/or the like. The characteristic may comprise atime of day, time of the month, season, and/or the like.

The characteristic group may be determined based on the request. Thecharacteristic group may be determined based on a characteristic of thefirst user. The characteristic group may be determined based on acharacteristic of the user device that transmitted the request. Thecharacteristic group may be determined based on a user interface contextassociated with initiating the request. The characteristic group may bedetermined based on other factors, such as timing, the content assetrequested, and/or the like.

At step 708, first data indicative of an association of the firstrepresentation with the characteristic group may be updated (e.g., bythe content device or other associated device). The first data maycomprise statistical information. The statistical information may beindicative of responses of a plurality of users to the firstrepresentation. Updating the first data may comprise updating (e.g.,incrementing, adding a value to or subtracting a value from, multiplyingor diving a number by) a user interaction metric associated with thefirst representation and associated with the characteristic group. Theuser interaction metric may comprise a count of a number of userinteractions (e.g., specific to users of the characteristic group)associated with the first representation. For example, the userinteraction metric may comprise a number of times any user associatedwith the characteristic group requested the content asset when the firstimage was used in the user interface to represent the content asset. Theuser interaction metric may comprise a number of times any userassociated with the characteristic group selected an interface element(e.g., a menu tile) comprising the first image to navigate to a pagedescribing the content asset. The user interaction metric may representpositive interactions, negative interactions (e.g., navigating past,navigating away from, navigating back to a menu), or may represent acombination of positive interactions and negative interactions.

The method 700 may further comprise determining to represent the contentasset by the first representation for the second user. The firstrepresentation may be determined based on being associated with ahighest statistical value of a plurality of representations associatedwith the characteristic group. The first representation may bedetermined by combining (e.g., averaging, adding, multiplying)statistical values associated with different characteristic groups. Forexample, more than one characteristic group may be determined for aparticular request, user, and/or the like.

At step 710, data indicative of the first representation of the contentasset may be transmitted (e.g., by the content device). The dataindicative of the first representation of the content asset may betransmitted to a user interface associated with a second user. The dataindicative of the first representation of the content asset may betransmitted based on the first data. Transmitting the data indicative ofthe first representation of the content asset may be based on thedetermining to represent the content asset by the first representationfor the second user. Determining to represent the content asset by thefirst representation for the second user may be based on the first data.

FIG. 8 depicts a computing device that may be used in various aspects,such as the servers, modules, and/or devices depicted in FIG. 1A andFIG. 1B. With regard to the example architecture of FIG. 1A-B, theinterface server 102, content server 108, and Local System 120(including modem 124 and local devices 128, 130, and 132) may each beimplemented in an instance of a computing device 800 of FIG. 8. Thecomputer architecture shown in FIG. 8 shows a conventional servercomputer, workstation, desktop computer, laptop, tablet, networkappliance, PDA, e-reader, digital cellular phone, or other computingnode, and may be utilized to execute any aspects of the computersdescribed herein, such as to implement the methods described in relationto FIG. 3A, FIG. 3B, FIG. 4, FIG. 5, FIG. 6, and FIG. 7.

The computing device 800 may include a baseboard, or “motherboard,”which is a printed circuit board to which a multitude of components ordevices may be connected by way of a system bus or other electricalcommunication paths. One or more central processing units (CPUs) 804 mayoperate in conjunction with a chipset 806. The CPU(s) 804 may bestandard programmable processors that perform arithmetic and logicaloperations necessary for the operation of the computing device 800.

The CPU(s) 804 may perform the necessary operations by transitioningfrom one discrete physical state to the next through the manipulation ofswitching elements that differentiate between and change these states.Switching elements may generally include electronic circuits thatmaintain one of two binary states, such as flip-flops, and electroniccircuits that provide an output state based on the logical combinationof the states of one or more other switching elements, such as logicgates. These basic switching elements may be combined to create morecomplex logic circuits including registers, adders-subtractors,arithmetic logic units, floating-point units, and the like.

The CPU(s) 804 may be augmented with or replaced by other processingunits, such as GPU(s) 805. The GPU(s) 805 may comprise processing unitsspecialized for but not necessarily limited to highly parallelcomputations, such as graphics and other visualization-relatedprocessing.

A chipset 806 may provide an interface between the CPU(s) 804 and theremainder of the components and devices on the baseboard. The chipset806 may provide an interface to a random access memory (RAM) 808 used asthe main memory in the computing device 800. The chipset 806 may furtherprovide an interface to a computer-readable storage medium, such as aread-only memory (ROM) 820 or non-volatile RAM (NVRAM) (not shown), forstoring basic routines that may help to start up the computing device800 and to transfer information between the various components anddevices. ROM 820 or NVRAM may also store other software componentsnecessary for the operation of the computing device 800 in accordancewith the aspects described herein.

The computing device 800 may operate in a networked environment usinglogical connections to remote computing nodes and computer systemsthrough local area network (LAN) 816. The chipset 806 may includefunctionality for providing network connectivity through a networkinterface controller (NIC) 822, such as a gigabit Ethernet adapter. ANIC 822 may be capable of connecting the computing device 800 to othercomputing nodes over a network 816. It should be appreciated thatmultiple NICs 822 may be present in the computing device 800, connectingthe computing device to other types of networks and remote computersystems.

The computing device 800 may be connected to a mass storage device 828that provides non-volatile storage for the computer. The mass storagedevice 828 may store system programs, application programs, otherprogram modules, and data, which have been described in greater detailherein. The mass storage device 828 may be connected to the computingdevice 800 through a storage controller 824 connected to the chipset806. The mass storage device 828 may consist of one or more physicalstorage units. A storage controller 824 may interface with the physicalstorage units through a serial attached SCSI (SAS) interface, a serialadvanced technology attachment (SATA) interface, a fiber channel (FC)interface, or other type of interface for physically connecting andtransferring data between computers and physical storage units.

The computing device 800 may store data on a mass storage device 828 bytransforming the physical state of the physical storage units to reflectthe information being stored. The specific transformation of a physicalstate may depend on various factors and on different implementations ofthis description. Examples of such factors may include, but are notlimited to, the technology used to implement the physical storage unitsand whether the mass storage device 828 is characterized as primary orsecondary storage and the like.

For example, the computing device 800 may store information to the massstorage device 828 by issuing instructions through a storage controller824 to alter the magnetic characteristics of a particular locationwithin a magnetic disk drive unit, the reflective or refractivecharacteristics of a particular location in an optical storage unit, orthe electrical characteristics of a particular capacitor, transistor, orother discrete component in a solid-state storage unit. Othertransformations of physical media are possible without departing fromthe scope and spirit of the present description, with the foregoingexamples provided only to facilitate this description. The computingdevice 800 may further read information from the mass storage device 828by detecting the physical states or characteristics of one or moreparticular locations within the physical storage units.

In addition to the mass storage device 828 described above, thecomputing device 500 may have access to other computer-readable storagemedia to store and retrieve information, such as program modules, datastructures, or other data. It should be appreciated by those skilled inthe art that computer-readable storage media may be any available mediathat provides for the storage of non-transitory data and that may beaccessed by the computing device 800.

By way of example and not limitation, computer-readable storage mediamay include volatile and non-volatile, transitory computer-readablestorage media and non-transitory computer-readable storage media, andremovable and non-removable media implemented in any method ortechnology. Computer-readable storage media includes, but is not limitedto, RAM, ROM, erasable programmable ROM (“EPROM”), electrically erasableprogrammable ROM (“EEPROM”), flash memory or other solid-state memorytechnology, compact disc ROM (“CD-ROM”), digital versatile disk (“DVD”),high definition DVD (“HD-DVD”), BLU-RAY, or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage, other magneticstorage devices, or any other medium that may be used to store thedesired information in a non-transitory fashion.

A mass storage device, such as the mass storage device 828 depicted inFIG. 8, may store an operating system utilized to control the operationof the computing device 800. The operating system may comprise a versionof the LINUX operating system. The operating system may comprise aversion of the WINDOWS SERVER operating system from the MICROSOFTCorporation. According to further aspects, the operating system maycomprise a version of the UNIX operating system. Various mobile phoneoperating systems, such as IOS and ANDROID, may also be utilized. Itshould be appreciated that other operating systems may also be utilized.The mass storage device 828 may store other system or applicationprograms and data utilized by the computing device 800.

The mass storage device 828 or other computer-readable storage media mayalso be encoded with computer-executable instructions, which, whenloaded into the computing device 800, transforms the computing devicefrom a general-purpose computing system into a special-purpose computercapable of implementing the aspects described herein. Thesecomputer-executable instructions transform the computing device 800 byspecifying how the CPU(s) 804 transition between states, as describedabove. The computing device 800 may have access to computer-readablestorage media storing computer-executable instructions, which, whenexecuted by the computing device 500, may perform the methods describedin relation to FIG. 3A, FIG. 3B, FIG. 4, FIG. 5, FIG. 6, and FIG. 7.

A computing device, such as the computing device 800 depicted in FIG. 8,may also include an input/output controller 832 for receiving andprocessing input from a number of input devices, such as a keyboard, amouse, a touchpad, a touch screen, an electronic stylus, or other typeof input device. Similarly, an input/output controller 832 may provideoutput to a display, such as a computer monitor, a flat-panel display, adigital projector, a printer, a plotter, or other type of output device.It will be appreciated that the computing device 800 may not include allof the components shown in FIG. 8, may include other components that arenot explicitly shown in FIG. 8, or may utilize an architecturecompletely different than that shown in FIG. 8.

As described herein, a computing device may be a physical computingdevice, such as the computing device 800 of FIG. 8. A computing node mayalso include a virtual machine host process and one or more virtualmachine instances. Computer-executable instructions may be executed bythe physical hardware of a computing device indirectly throughinterpretation and/or execution of instructions stored and executed inthe context of a virtual machine.

It is to be understood that the methods and systems are not limited tospecific methods, specific components, or to particular implementations.It is also to be understood that the terminology used herein is for thepurpose of describing particular embodiments only and is not intended tobe limiting.

As used in the specification and the appended claims, the singular forms“a,” “an,” and “the” include plural referents unless the context clearlydictates otherwise. Ranges may be expressed herein as from “about” oneparticular value, and/or to “about” another particular value. When sucha range is expressed, another embodiment includes from the oneparticular value and/or to the other particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms anotherembodiment. It will be further understood that the endpoints of each ofthe ranges are significant both in relation to the other endpoint, andindependently of the other endpoint.

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where said event or circumstance occurs and instances where itdoes not.

Throughout the description and claims of this specification, the word“comprise” and variations of the word, such as “comprising” and“comprises,” means “including but not limited to,” and is not intendedto exclude, for example, other components, integers or steps.“Exemplary” means “an example of” and is not intended to convey anindication of a preferred or ideal embodiment. “Such as” is not used ina restrictive sense, but for explanatory purposes.

Components are described that may be used to perform the describedmethods and systems. When combinations, subsets, interactions, groups,etc., of these components are described, it is understood that whilespecific references to each of the various individual and collectivecombinations and permutations of these may not be explicitly described,each is specifically contemplated and described herein, for all methodsand systems. This applies to all aspects of this application including,but not limited to, operations in described methods. Thus, if there area variety of additional operations that may be performed it isunderstood that each of these additional operations may be performedwith any specific embodiment or combination of embodiments of thedescribed methods.

The present methods and systems may be understood more readily byreference to the following detailed description of preferred embodimentsand the examples included therein and to the Figures and theirdescriptions.

As will be appreciated by one skilled in the art, the methods andsystems may take the form of an entirely hardware embodiment, anentirely software embodiment, or an embodiment combining software andhardware aspects. Furthermore, the methods and systems may take the formof a computer program product on a computer-readable storage mediumhaving computer-readable program instructions (e.g., computer software)embodied in the storage medium. More particularly, the present methodsand systems may take the form of web-implemented computer software. Anysuitable computer-readable storage medium may be utilized including harddisks, CD-ROMs, optical storage devices, or magnetic storage devices.

Embodiments of the methods and systems are described below withreference to block diagrams and flowchart illustrations of methods,systems, apparatuses and computer program products. It will beunderstood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, respectively, may be implemented by computerprogram instructions. These computer program instructions may be loadedon a general-purpose computer, special-purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus create a means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that may direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the function specified in the flowchartblock or blocks. The computer program instructions may also be loadedonto a computer or other programmable data processing apparatus to causea series of operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and sub-combinations are intended to fall withinthe scope of this disclosure. In addition, certain methods or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto may be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically described, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe described example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the described example embodiments.

It will also be appreciated that various items are illustrated as beingstored in memory or on storage while being used, and that these items orportions thereof may be transferred between memory and other storagedevices for purposes of memory management and data integrity.Alternatively, in other embodiments, some or all of the software modulesand/or systems may execute in memory on another device and communicatewith the illustrated computing systems via inter-computer communication.Furthermore, in some embodiments, some or all of the systems and/ormodules may be implemented or provided in other ways, such as at leastpartially in firmware and/or hardware, including, but not limited to,one or more application-specific integrated circuits (“ASICs”), standardintegrated circuits, controllers (e.g., by executing appropriateinstructions, and including microcontrollers and/or embeddedcontrollers), field-programmable gate arrays (“FPGAs”), complexprogrammable logic devices (“CPLDs”), etc. Some or all of the modules,systems, and data structures may also be stored (e.g., as softwareinstructions or structured data) on a computer-readable medium, such asa hard disk, a memory, a network, or a portable media article to be readby an appropriate device or via an appropriate connection. The systems,modules, and data structures may also be transmitted as generated datasignals (e.g., as part of a carrier wave or other analog or digitalpropagated signal) on a variety of computer-readable transmission media,including wireless-based and wired/cable-based media, and may take avariety of forms (e.g., as part of a single or multiplexed analogsignal, or as multiple discrete digital packets or frames). Suchcomputer program products may also take other forms in otherembodiments. Accordingly, the present invention may be practiced withother computer system configurations.

While the methods and systems have been described in connection withpreferred embodiments and specific examples, it is not intended that thescope be limited to the particular embodiments set forth, as theembodiments herein are intended in all respects to be illustrativerather than restrictive.

Unless otherwise expressly stated, it is in no way intended that anymethod set forth herein be construed as requiring that its operations beperformed in a specific order. Accordingly, where a method claim doesnot actually recite an order to be followed by its operations or it isnot otherwise specifically stated in the claims or descriptions that theoperations are to be limited to a specific order, it is no way intendedthat an order be inferred, in any respect. This holds for any possiblenon-express basis for interpretation, including: matters of logic withrespect to arrangement of steps or operational flow; plain meaningderived from grammatical organization or punctuation; and the number ortype of embodiments described in the specification.

It will be apparent to those skilled in the art that variousmodifications and variations may be made without departing from thescope or spirit of the present disclosure. Other embodiments will beapparent to those skilled in the art from consideration of thespecification and practices described herein. It is intended that thespecification and example figures be considered as exemplary only, witha true scope and spirit being indicated by the following claims.

What is claimed:
 1. A method comprising: receiving, from a userinterface associated with a first user, a request for interface data;determining, based on the request, a first content asset to representvia the user interface and a second content asset to represent via theuser interface; determining, for the first content asset and based on afirst type of content associated with the first content asset, a firstplurality of characteristic groups; determining, for the second contentasset and based on a second type of content associated with the secondcontent asset, a second plurality of characteristic groups differentthan the first plurality of characteristic groups; determining, for eachof the first content asset and the second content asset, statisticalinformation comprising data indicating responses of a plurality of usersto a plurality of images, wherein the statistical information for thefirst content asset categorizes corresponding responses based on thefirst plurality of characteristic groups and the statistical informationfor the second content asset categorizes corresponding responses basedon the second plurality of characteristic groups; and causing, based onthe statistical information, the user interface to output for the firstuser a first image, of the plurality of images, representing the firstcontent asset and a second image, of the plurality of images,representing the second content asset.
 2. The method of claim 1, whereinthe first plurality of characteristic groups comprises one or more of auser affinity group or a user interest group.
 3. The method of claim 1,further comprising determining, based on user information associatedwith the first user, one or more of the first plurality ofcharacteristic groups that are associated with the first user, whereinthe first image is caused to be output based on the first user matchingthe one or more of the first plurality of characteristic groups.
 4. Themethod of claim 1, wherein receiving, from the user interface associatedwith the first user, the request for the interface data comprisesreceiving a request for the interface data to update a menu or a page ofthe user interface associated with the first user.
 5. The method ofclaim 1, wherein the first type of content comprises news content andthe second type of content comprises one or more of sports content orcontent different than news content.
 6. The method of claim 1, furthercomprising combining, for each of one or more images, counts in thestatistical information corresponding to a portion of the firstplurality of characteristic groups that match the first user, whereincausing output of the first image is based on the first image having alarger number of counts than other images of the one or more images. 7.The method of claim 1, wherein the second plurality of characteristicgroups comprise one or more of a device type, a user interface version,an operating system, or a user interface context.
 8. A device comprisingone or more processors; and memory storing instructions that, whenexecuted by the one or more processors, cause the device to: receive,from a user interface associated with a first user, a request forinterface data; determine, based on the request, a first content assetto represent via the user interface and a second content asset torepresent via the user interface; determine, for the first content assetand based on a first type of content associated with the first contentasset, a first plurality of characteristic groups; determine, for thesecond content asset and based on a second type of content associatedwith the second content asset, a second plurality of characteristicgroups different than the first plurality of characteristic groups;determine, for each of the first content asset and the second contentasset, statistical information comprising data indicating responses of aplurality of users to a plurality of images, wherein the statisticalinformation for the first content asset categorizes correspondingresponses based on the first plurality of characteristic groups and thestatistical information for the second content asset categorizescorresponding responses based on the second plurality of characteristicgroups; and cause, based on the statistical information, the userinterface to output for the first user a first image, of the pluralityof images, representing the first content asset and a second image, ofthe plurality of images, representing the second content asset.
 9. Thedevice of claim 8, wherein the first plurality of characteristic groupscomprises one or more of a user affinity group or a user interest group.10. The device of claim 8, wherein the instructions, when executed bythe one or more processors, further cause the device to determine, basedon user information associated with the first user, one or more of thefirst plurality of characteristic groups that are associated with thefirst user, wherein output of the first image is caused based on thefirst user matching the one or more of the first plurality ofcharacteristic groups.
 11. The device of claim 8, wherein theinstructions that, when executed by the one or more processors, causethe device to receive, from the user interface associated with the firstuser, the request for the interface data comprises instructions that,when executed by the one or more processors, cause the device to receivea request for the interface data to update a menu or a page of the userinterface associated with the first user.
 12. The device of claim 8,wherein the first type of content comprises news content and the secondtype of content comprises one or more of sports content or contentdifferent than news content.
 13. The device of claim 8, wherein theinstructions, when executed by the one or more processors, further causethe device to combine, for each of one or more images, counts in thestatistical information corresponding to a portion of the firstplurality of characteristic groups that match the first user, whereinoutput of the first image is caused based on the first image having alarger number of counts than other images of the one or more images. 14.The device of claim 8, wherein the second plurality of characteristicgroups comprise one or more of a device type, a user interface version,an operating system, or a user interface context.
 15. A non-transitorycomputer-readable medium storing computer-executable instructions that,when executed, cause: receiving, from a user interface associated with afirst user, a request for interface data; determining, based on therequest, a first content asset to represent via the user interface and asecond content asset to represent via the user interface; determining,for the first content asset and based on a first type of contentassociated with the first content asset, a first plurality ofcharacteristic groups; determining, for the second content asset andbased on a second type of content associated with the second contentasset, a second plurality of characteristic groups different than thefirst plurality of characteristic groups; determining, for each of thefirst content asset and the second content asset, statisticalinformation comprising data indicating responses of a plurality of usersto a plurality of images, wherein the statistical information for thefirst content asset categorizes corresponding responses based on thefirst plurality of characteristic groups and the statistical informationfor the second content asset categorizes corresponding responses basedon the second plurality of characteristic groups; and causing, based onthe statistical information, the user interface to output for the firstuser a first image, of the plurality of images, representing the firstcontent asset and a second image, of the plurality of images,representing the second content asset.
 16. The non-transitorycomputer-readable medium of claim 15, wherein the first plurality ofcharacteristic groups comprises one or more of a user affinity group ora user interest group.
 17. The non-transitory computer-readable mediumof claim 15, wherein the instructions, when executed, further causedetermining, based on user information associated with the first user,one or more of the first plurality of characteristic groups that areassociated with the first user, wherein the first image is caused to beoutput based on the first user matching the one or more of the firstplurality of characteristic groups.
 18. The non-transitorycomputer-readable medium of claim 15, wherein receiving, from the userinterface associated with the first user, the request for the interfacedata comprises receiving a request for the interface data to update amenu or a page of the user interface associated with the first user. 19.The non-transitory computer-readable medium of claim 15, wherein thefirst type of content comprises news content and the second type ofcontent comprises one or more of sports content or content differentthan news content.
 20. The non-transitory computer-readable medium ofclaim 15, wherein the instructions, when executed, further causecombining, for each of one or more images, counts in the statisticalinformation corresponding to a portion of the first plurality ofcharacteristic groups that match the first user, wherein causing outputof the first image is based on the first image having a larger number ofcounts than other images of the one or more images.
 21. Thenon-transitory computer-readable medium of claim 15, wherein the secondplurality of characteristic groups comprise one or more of a devicetype, a user interface version, an operating system, or a user interfacecontext.
 22. A system comprising: a first computing device configured tostore a plurality of content assets; and a second computing deviceconfigured to: receive, from a user interface associated with a firstuser, a request for interface data; determine, based on the request, afirst content asset of the plurality of content assets to represent viathe user interface and a second content asset of the plurality ofcontent assets to represent via the user interface; determine, for thefirst content asset and based on a first type of content associated withthe first content asset, a first plurality of characteristic groups;determine, for the second content asset and based on a second type ofcontent associated with the second content asset, a second plurality ofcharacteristic groups different than the first plurality ofcharacteristic groups; determine, for each of the first content assetand the second content asset, statistical information comprising dataindicating responses of a plurality of users to a plurality of images,wherein the statistical information for the first content assetcategorizes corresponding responses based on the first plurality ofcharacteristic groups and the statistical information for the secondcontent asset categorizes corresponding responses based on the secondplurality of characteristic groups; and cause, based on the statisticalinformation, the user interface to output for the first user a firstimage, of the plurality of images, representing the first content assetand a second image, of the plurality of images, representing the secondcontent asset.
 23. The system of claim 22, wherein the first pluralityof characteristic groups comprises one or more of a user affinity groupor a user interest group.
 24. The system of claim 22, wherein the secondcomputing device is further configured to determine, based on userinformation associated with the first user, one or more of the firstplurality of characteristic groups that are associated with the firstuser, wherein the first image is caused to be output based on the firstuser matching the one or more of the first plurality of characteristicgroups.
 25. The system of claim 22, wherein the second computing deviceis further configured to receive, from the user interface associatedwith the first user, the request for interface data by receiving arequest for the interface data to update a menu or a page of the userinterface associated with the first user.
 26. The system of claim 22,wherein the first type of content comprises news content and the secondtype of content comprises one or more of sports content or contentdifferent than news content.
 27. The system of claim 22, wherein thesecond computing device is further configured to combine, for each ofone or more images, counts in the statistical information correspondingto a portion of the first plurality of characteristic groups that matchthe first user, wherein the second computing device is configured tocause output of the first image based on the first image having a largernumber of counts than other images of the one or more images.
 28. Thesystem of claim 22, wherein the second plurality of characteristicgroups comprise one or more of a device type, a user interface version,an operating system, or a user interface context.